1. Field of the Invention
The present invention relates to pattern recognition and statistics etc., more particularly to a method for multiple feature fusion personal identity recognition based on eye images.
2. Description of Prior Art
Personal identity feature is the basic information of a human being, which is very important. However, it is hard for a knowledge- and material-based identity recognition technology, such as password, secret code, and ID card, to fulfill the requirements of large-scale application and high level of security, and such technologies bring inconvenience to users. With the increasing development of intelligence- and information-based technologies in our society, a large-scale identify recognition technology has a great contribution on national security, public security, economic security and network security. Biometrics technology is a technology for identity recognition by using physical and behavior features of a human being, and has advantages such as high accuracy, high convenience for use, and high security. Widely used existing biometric modes include face recognition, iris recognition, voice recognition, fingerprint recognition, palm print recognition, signature, and gait recognition etc. Corresponding biometric systems are also successfully applied in various fields such as access control and network security etc.
Most of the existing biometric technologies require a well cooperation by the users. For example, most of fingerprint and palm print recognition devices are contact devices, while a non-contact device requires the user to corporate in a fixed manner. On one hand, inconvenience is introduced to the user, the system recognition rate is reduced, and the requirements of low response time and high flow volume in a large scale recognition scenario such as an air port, a customhouse, or a station etc.); on the other hand, the system can only operates in a passive recognition mode due to such well cooperation, in other words, the sensor can only receive data passively. However most of the security scenarios require an active recognition in which the sensor may obtain the information of the user with no or little corporation of the user. For example, it is desirable to authenticate the identity of a person in the monitor scenario in real time without any corporate of the user. Although some modes, such as face and gait, can be used in identity recognition without any cooperation of the user, the recognition accuracy of face recognition and gait recognition is not sufficient to fulfill the practical requirements.
Human eye region contains pupil, iris, eyelid, periocular skin, eyebrow, eyelash, and etc. Iris has been proved to be one of the most accurate biometric trait due to the high uniqueness of its texture. Iris recognition systems have also been applied in public places like bank, customs, airport, coal mine, as well for the social affairs like welfare distribution, missing children finding, and so on. In addition to iris texture, texture of periocular skin has good decidability and thus can be used for identity recognition. In addition, iris and eye skin region will render a color characteristic under visible light, and thus can be taken as assistant features. For example, in additional to appearance feature, the eye region has significant semantic features such as left/right eye, double/single-edged eyelid, profile of eyelid, and so on, which may also be classified. Therefore, the eye region becomes a biometric trait with the best decidability due to its various features.
Besides the high uniqueness, biometric trait based on eye region is also a biometric trait which is easy to be used and populated. Eye is a visual organ for human to sense the world, so that the eye region is generally exposed to the outside. Even when the face is shield, eye region is still uncovered. Therefore the eye region is easy to be captured by a visual sensor such as a camera. With the development of optical imaging technology, an active imaging system becomes possible. Related systems can acquire clear eye images from ten meters away or even more. In view of the above, identity recognition based on eye image can achieve a user-friendly man-machine interaction and active recognition functions.
Moreover, identity recognition based on eye region is very robust. A single modal biometric system is limited by application scenarios. For example, an iris texture suffering from disease is unable to be used in iris recognition. Because eye region contains multiple biometric trait modes such as iris texture and skin texture, the multimode biometric traits can be applied in various scenarios with few limitations.
In existing patents, a iris recognition system based on the uniqueness of iris is used for identity recognition by using eye region information, in which other features of the eye is not used. In addition, all the existing patents related to iris recognition achieve identity authentication by analyzing the local characteristic of iris texture feature of eye, such as the iris recognition algorithm proposed by Dr. John Daugman of University of Cambridge (U.S. Pat. No. 5,291,560), in which feature coding is performed by a Cabor filter; the method for iris recognition by analyzing shape feature of iris blobs proposed by Prof. Tieniu Tan et al. (CN 1684095). These methods are vulnerable to noise and rely on the accuracy of iris segmentation.
Sparse coding based iris recognition method in this patent is robust to the environmental noises, and does not ask for an additional noise detection based on image segmentation. Furthermore, in traditional score level fusion, the affections by the distribution of scores and the data noise is not considered, and thus the complementary characteristic between respective modes are not fully used.